Task Description

PSU researchers shall apply the newly incorporated mode shift module (in the updated RSPM tool) in the Corvallis Area Metropolitan Planning Organization (CAMPO) to assess how it can inform decision-making and to adjust the model as needed to provide accurate and helpful information. ODOT staff will assist in assembling the necessary data for sensitivity test. Initial testing will be documented by the PSU researchers.

The phases of the testing task are:

Phase 1: Test modules on their own using SLD/NHTS data used in estimation; Test module sensitivity, vary SLD/NHTS inputs one at a time – elasticity response vs. Literature VMT, PMT by mode, total and split by HH income, density, urban form groups

Phase 2: Test module in RVMPO RSPM (using a code wrapper and supplemental RVMPO block group place type inputs) comparing current vs. new outputs, VMT/Alt mode trips at MPO/district geographies (maps) and HH attributes (place types, income, …) – tests full model performance improvement over existing tool using built form variables

Phase 3: Test module in VisionEval (written up to 1st call of this module) – tests to see if module will work in future VisionEval tool

Phase I

For Phase I of Task 4, elasticities of AADVMT and PMT with regard to density (D1B), household income, freeway supply (Freeway lane miles per caipta), transit supply (transit revenue miles per capita) are computed using the 2009 NHTS data. Except for a few unexpected couterintuitive direction of elasticities (bike PMT elasticities wrt D1B), the elasticities are inline with what has been documented in research literature: travel behavior responses to density change is small in magitude. Given the non-linear nature of the models, the elasticities vary by different segments - such as income group, development type, and current density level. Those segments are adopted from what Brian Gregor used in his sensitivity testing for GreenSTEP.

Annual Average Daily VMT (AADVMT)

Model Specification

The specification for the AADVMT model has been documented in Task2. It is replicated here for quick reference.

AADVMT model
metro nonmetro
(1) (2)
Drivers 0.705*** 0.744***
(0.009) (0.010)
HhSize 0.017**
(0.008)
Workers 0.186*** 0.177***
(0.008) (0.007)
LogIncome 0.268*** 0.288***
(0.007) (0.006)
Age0to14 0.107*** 0.102***
(0.010) (0.011)
Age65Plus -0.075*** -0.077***
(0.009) (0.007)
log1p(VehPerDriver) 1.790*** 1.850***
(0.028) (0.020)
LifeCycleCouple w/o children -0.036** -0.013
(0.016) (0.016)
LifeCycleEmpty Nester -0.256*** -0.208***
(0.018) (0.019)
LifeCycleSingle -0.234*** -0.216***
(0.022) (0.023)
CENSUS_RNE -0.109*** -0.112***
(0.023) (0.017)
CENSUS_RS 0.051** 0.058***
(0.021) (0.014)
CENSUS_RW -0.092*** -0.176***
(0.021) (0.017)
FwyLaneMiPC 101.000***
(21.400)
D1B -0.003*** -0.008***
(0.0003) (0.003)
D2A_WRKEMP -0.0002*
(0.0001)
D3bpo4 -0.001***
(0.0002)
TranRevMiPC:D4c -0.020***
(0.003)
D2A_EPHHM -0.084***
(0.022)
D1B:D2A_EPHHM -0.027***
(0.006)
Constant -1.330*** -1.420***
(0.079) (0.065)
Observations 42,721 61,190
R2 0.446 0.460
Adjusted R2 0.446 0.459
Residual Std. Error 0.987 (df = 42703) 1.010 (df = 61173)
F Statistic 2,026.000*** (df = 17; 42703) 3,251.000*** (df = 16; 61173)
Note: p<0.1; p<0.05; p<0.01

Population Density (D1B) Sensitivity

Both the table and figures below demonstrate small negative elasticities of AADVMT to local population density (D1B from Smart Location Database population density at block group level). Non-metropolitan areas have larger elasticities; higher density areas have larger elasticities, and TODs have larger elasticities.

  Δ AADVMT wrt Δ D1B
metro Category n AADVMT   +10% +20% +30% +40% +50%
overall
metro 72913 46.8   -0.075 -0.151 -0.227 -0.296 -0.365
non_metro 65023 55.8   -0.102 -0.201 -0.300 -0.397 -0.494
population_per_sqm
metro <1k 7755 55.3   -0.009 -0.018 -0.026 -0.035 -0.044
metro 1k-5k 38783 50.8   -0.040 -0.081 -0.121 -0.161 -0.201
metro 5k-10k 18000 46.3   -0.089 -0.178 -0.267 -0.356 -0.445
metro >10k 8375 33.4   -0.186 -0.374 -0.560 -0.718 -0.879
non_metro <1k 45003 58.9   -0.025 -0.050 -0.074 -0.099 -0.124
non_metro 1k-5k 16470 49.8   -0.219 -0.437 -0.654 -0.871 -1.086
non_metro 5k-10k 3101 45.0   -0.500 -0.982 -1.473 -1.961 -2.417
non_metro >10k 449 31.2   -0.758 -1.432 -2.027 -2.546 -3.184
Income
metro <$40k 26484 26.1   -0.056 -0.114 -0.171 -0.220 -0.268
metro $40k-$80k 22503 47.3   -0.083 -0.166 -0.248 -0.326 -0.408
metro >$80k 23926 65.6   -0.094 -0.187 -0.280 -0.372 -0.464
non_metro <$40k 27719 36.3   -0.075 -0.147 -0.218 -0.287 -0.357
non_metro $40k-$80k 21443 63.1   -0.108 -0.216 -0.323 -0.430 -0.536
non_metro >$80k 15861 80.0   -0.140 -0.278 -0.417 -0.554 -0.692
DevelopmentType
metro Employment 13440 47.4   -0.044 -0.089 -0.133 -0.178 -0.222
metro Low Density/Rural 7204 57.1   -0.026 -0.051 -0.077 -0.103 -0.129
metro Mixed 4183 41.7   -0.087 -0.173 -0.259 -0.345 -0.431
metro Mixed High 998 31.5   -0.126 -0.285 -0.440 -0.555 -0.668
metro Residential 46503 46.9   -0.085 -0.169 -0.253 -0.329 -0.406
metro TOD 585 26.6   -0.172 -0.341 -0.509 -0.674 -0.837
non_metro Employment 11873 51.8   -0.142 -0.279 -0.415 -0.554 -0.693
non_metro Low Density/Rural 37061 59.4   -0.029 -0.057 -0.086 -0.113 -0.141
non_metro Mixed 356 39.9   -0.454 -0.903 -1.346 -1.568 -2.002
non_metro Mixed High 80 31.8   -0.487 -0.966 -1.436 -1.898 -2.352
non_metro Residential 15647 50.7   -0.234 -0.463 -0.691 -0.921 -1.140
non_metro TOD 6 27.0   -0.544 -1.071 -1.583 -2.080 -2.562

Household Income Sensitivity

As expected, household income has positive elasticities to AADVMT. The elasticities to income is most stable across segments.

  Δ AADVMT wrt Δ income
metro Category n AADVMT   +10% +20% +30% +40% +50%
overall
metro 72913 46.8   0.695 1.335 1.930 2.480 3.000
non_metro 65023 55.8   0.839 1.614 2.330 3.000 3.630
population_per_sqm
metro <1k 7755 55.3   0.785 1.507 2.180 2.800 3.390
metro 1k-5k 38783 50.8   0.742 1.425 2.060 2.650 3.200
metro 5k-10k 18000 46.3   0.695 1.335 1.930 2.480 3.000
metro >10k 8375 33.4   0.533 1.028 1.470 1.900 2.300
non_metro <1k 45003 58.9   0.873 1.677 2.420 3.120 3.770
non_metro 1k-5k 16470 49.8   0.780 1.498 2.170 2.790 3.370
non_metro 5k-10k 3101 45.0   0.726 1.395 2.020 2.600 3.140
non_metro >10k 449 31.2   0.499 1.024 1.510 1.890 2.320
Income
metro <$40k 26484 26.1   0.470 0.905 1.300 1.680 2.040
metro $40k-$80k 22503 47.3   0.716 1.377 1.990 2.560 3.100
metro >$80k 23926 65.6   0.888 1.705 2.460 3.170 3.830
non_metro <$40k 27719 36.3   0.636 1.224 1.770 2.280 2.760
non_metro $40k-$80k 21443 63.1   0.925 1.778 2.570 3.310 4.000
non_metro >$80k 15861 80.0   1.080 2.073 2.990 3.850 4.660
DevelopmentType
metro Employment 13440 47.4   0.705 1.355 1.960 2.520 3.050
metro Low Density/Rural 7204 57.1   0.803 1.543 2.230 2.870 3.470
metro Mixed 4183 41.7   0.646 1.242 1.790 2.310 2.790
metro Mixed High 998 31.5   0.490 0.938 1.390 1.810 2.200
metro Residential 46503 46.9   0.695 1.337 1.930 2.480 3.000
metro TOD 585 26.6   0.466 0.896 1.200 1.570 1.870
non_metro Employment 11873 51.8   0.797 1.532 2.210 2.850 3.450
non_metro Low Density/Rural 37061 59.4   0.878 1.687 2.440 3.140 3.790
non_metro Mixed 356 39.9   0.549 1.160 1.730 2.260 2.750
non_metro Mixed High 80 31.8   0.575 1.106 1.600 1.640 2.070
non_metro Residential 15647 50.7   0.789 1.516 2.190 2.820 3.410
non_metro TOD 6 27.0   0.509 0.980 1.420 1.830 2.210

Freeway Supply Sensitivity

Also corraborating previous research and Brian’s finding, the elasticities to freeway supply is positive but small, mostly because most places in the US already have good mobility by vehicle, additional freeways lead households to drive slightly more miles.

  Δ AADVMT wrt Δ FwyLaneMiPC
metro Category n AADVMT   +10% +20% +30% +40% +50%
overall
metro 72913 46.8   0.172 0.344 0.515 0.688 0.862
population_per_sqm
metro <1k 7755 55.3   0.227 0.454 0.682 0.911 1.141
metro 1k-5k 38783 50.8   0.190 0.380 0.571 0.763 0.955
metro 5k-10k 18000 46.3   0.162 0.324 0.486 0.649 0.812
metro >10k 8375 33.4   0.116 0.231 0.343 0.460 0.576
Income
metro <$40k 26484 26.1   0.116 0.233 0.348 0.465 0.583
metro $40k-$80k 22503 47.3   0.178 0.357 0.536 0.715 0.895
metro >$80k 23926 65.6   0.218 0.436 0.654 0.873 1.093
DevelopmentType
metro Employment 13440 47.4   0.182 0.364 0.547 0.730 0.914
metro Low Density/Rural 7204 57.1   0.220 0.441 0.662 0.884 1.107
metro Mixed 4183 41.7   0.148 0.297 0.445 0.595 0.744
metro Mixed High 998 31.5   0.115 0.229 0.345 0.460 0.576
metro Residential 46503 46.9   0.169 0.338 0.507 0.677 0.848
metro TOD 585 26.6   0.103 0.205 0.309 0.412 0.516

Transit Supply Sensitivity

As expected, transit supply (transit revenue miles per captia) has negative elasticities to AADVMT. The elasticities are inline with Brian’s numbers. And elasticities are larger for dense areas and for TODs.

  Δ AADVMT wrt Δ TranRevMiPC
metro Category n AADVMT   +10% +20% +30% +40% +50%
overall
metro 72913 46.8   -0.033 -0.068 -0.103 -0.135 -0.167
population_per_sqm
metro <1k 7755 55.3   -0.010 -0.020 -0.031 -0.041 -0.051
metro 1k-5k 38783 50.8   -0.020 -0.041 -0.061 -0.081 -0.101
metro 5k-10k 18000 46.3   -0.037 -0.074 -0.112 -0.148 -0.185
metro >10k 8375 33.4   -0.074 -0.157 -0.238 -0.306 -0.378
Income
metro <$40k 26484 26.1   -0.024 -0.052 -0.080 -0.102 -0.126
metro $40k-$80k 22503 47.3   -0.034 -0.069 -0.103 -0.137 -0.171
metro >$80k 23926 65.6   -0.043 -0.085 -0.128 -0.170 -0.211
DevelopmentType
metro Employment 13440 47.4   -0.030 -0.060 -0.090 -0.120 -0.149
metro Low Density/Rural 7204 57.1   -0.005 -0.009 -0.014 -0.018 -0.023
metro Mixed 4183 41.7   -0.071 -0.142 -0.213 -0.283 -0.353
metro Mixed High 998 31.5   -0.028 -0.092 -0.155 -0.183 -0.246
metro Residential 46503 46.9   -0.029 -0.060 -0.090 -0.118 -0.147
metro TOD 585 26.6   -0.301 -0.598 -0.890 -1.178 -1.418

Bike PMT

Model specification

The specification for the Bike PMT model has been documented in Task2. Here it is replicated for a quick reference.

## $metro
## 
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Bike) ~ AADVMT + Workers + 
##     LogIncome + LifeCycle + Age0to14 + CENSUS_R + FwyLaneMiPC + 
##     D4c + TranRevMiPC:D4c + D1B + D3apo | AADVMT + LogIncome + Workers + 
##     LifeCycle + Age0to14 + CENSUS_R + D1B + D2A_EPHHM + D5 + FwyLaneMiPC + 
##     TranRevMiPC, data = ., na.action = na.exclude, weights = .$hhwgt)
## 
## Pearson residuals:
##     Min      1Q  Median      3Q     Max 
## -2.1930 -0.1560 -0.0898 -0.0513 78.2903 
## 
## Count model coefficients (truncated poisson with log link):
##                                 Estimate  Std. Error z value
## (Intercept)                    -1.156170    0.193752   -5.97
## AADVMT                          0.000925    0.000243    3.80
## Workers                         0.151733    0.014670   10.34
## LogIncome                       0.200522    0.016369   12.25
## LifeCycleCouple w/o children    0.513038    0.029628   17.32
## LifeCycleEmpty Nester           0.202835    0.045990    4.41
## LifeCycleSingle                 0.231229    0.060025    3.85
## Age0to14                       -0.123288    0.014875   -8.29
## CENSUS_RNE                     -0.088683    0.047491   -1.87
## CENSUS_RS                       0.198412    0.033456    5.93
## CENSUS_RW                       0.189267    0.031299    6.05
## FwyLaneMiPC                  -164.434920   55.699729   -2.95
## D4c                            -0.001398    0.000326   -4.29
## D1B                            -0.004317    0.000785   -5.50
## D3apo                           0.017603    0.001955    9.01
## D4c:TranRevMiPC                 0.111221    0.012385    8.98
##                                          Pr(>|z|)    
## (Intercept)                          0.0000000024 ***
## AADVMT                                    0.00014 ***
## Workers                      < 0.0000000000000002 ***
## LogIncome                    < 0.0000000000000002 ***
## LifeCycleCouple w/o children < 0.0000000000000002 ***
## LifeCycleEmpty Nester                0.0000103191 ***
## LifeCycleSingle                           0.00012 ***
## Age0to14                     < 0.0000000000000002 ***
## CENSUS_RNE                                0.06185 .  
## CENSUS_RS                            0.0000000030 ***
## CENSUS_RW                            0.0000000015 ***
## FwyLaneMiPC                               0.00316 ** 
## D4c                                  0.0000174944 ***
## D1B                                  0.0000000388 ***
## D3apo                        < 0.0000000000000002 ***
## D4c:TranRevMiPC              < 0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
##                                 Estimate  Std. Error z value
## (Intercept)                    -4.055517    0.425400   -9.53
## AADVMT                         -0.003556    0.000728   -4.88
## LogIncome                       0.084590    0.037258    2.27
## Workers                         0.333631    0.036441    9.16
## LifeCycleCouple w/o children   -0.495908    0.077771   -6.38
## LifeCycleEmpty Nester          -0.839034    0.105981   -7.92
## LifeCycleSingle                -1.503947    0.136814  -10.99
## Age0to14                        0.422132    0.029329   14.39
## CENSUS_RNE                     -0.752382    0.102230   -7.36
## CENSUS_RS                      -0.018906    0.075344   -0.25
## CENSUS_RW                       0.217610    0.073261    2.97
## D1B                            -0.006395    0.002121   -3.02
## D2A_EPHHM                       0.231721    0.118776    1.95
## D5                              0.026053    0.005287    4.93
## FwyLaneMiPC                  -563.361545  129.407192   -4.35
## TranRevMiPC                    -6.785162    2.628698   -2.58
##                                          Pr(>|z|)    
## (Intercept)                  < 0.0000000000000002 ***
## AADVMT                         0.0000010493363211 ***
## LogIncome                                  0.0232 *  
## Workers                      < 0.0000000000000002 ***
## LifeCycleCouple w/o children   0.0000000001811333 ***
## LifeCycleEmpty Nester          0.0000000000000024 ***
## LifeCycleSingle              < 0.0000000000000002 ***
## Age0to14                     < 0.0000000000000002 ***
## CENSUS_RNE                     0.0000000000001843 ***
## CENSUS_RS                                  0.8019    
## CENSUS_RW                                  0.0030 ** 
## D1B                                        0.0026 ** 
## D2A_EPHHM                                  0.0511 .  
## D5                             0.0000008322243770 ***
## FwyLaneMiPC                    0.0000134040952526 ***
## TranRevMiPC                                0.0098 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
## 
## Number of iterations in BFGS optimization: 63 
## Log-likelihood: -1.29e+04 on 32 Df
## 
## $non_metro
## 
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Bike) ~ AADVMT + HhSize + 
##     LogIncome + HhSize + LifeCycle + Age0to14 + Age65Plus + D1B + 
##     D3bpo4 | AADVMT + LogIncome + Workers + LifeCycle + Age0to14 + 
##     D1B + D2A_EPHHM + D3bpo4, data = ., na.action = na.exclude, 
##     weights = .$hhwgt)
## 
## Pearson residuals:
##      Min       1Q   Median       3Q      Max 
##  -1.8557  -0.1141  -0.0641  -0.0381 126.8273 
## 
## Count model coefficients (truncated poisson with log link):
##                               Estimate Std. Error z value
## (Intercept)                  -3.583887   0.249132  -14.39
## AADVMT                        0.000473   0.000218    2.17
## HhSize                        0.123153   0.014044    8.77
## LogIncome                     0.414544   0.020972   19.77
## LifeCycleCouple w/o children  0.831324   0.041390   20.09
## LifeCycleEmpty Nester         0.642947   0.051906   12.39
## LifeCycleSingle               0.709623   0.063863   11.11
## Age0to14                     -0.254262   0.021604  -11.77
## Age65Plus                     0.217058   0.024878    8.72
## D1B                           0.010425   0.003947    2.64
## D3bpo4                        0.005256   0.000481   10.93
##                                         Pr(>|z|)    
## (Intercept)                  <0.0000000000000002 ***
## AADVMT                                    0.0303 *  
## HhSize                       <0.0000000000000002 ***
## LogIncome                    <0.0000000000000002 ***
## LifeCycleCouple w/o children <0.0000000000000002 ***
## LifeCycleEmpty Nester        <0.0000000000000002 ***
## LifeCycleSingle              <0.0000000000000002 ***
## Age0to14                     <0.0000000000000002 ***
## Age65Plus                    <0.0000000000000002 ***
## D1B                                       0.0083 ** 
## D3bpo4                       <0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
##                              Estimate Std. Error z value
## (Intercept)                  -6.70698    0.43666  -15.36
## AADVMT                       -0.00359    0.00065   -5.53
## LogIncome                     0.30930    0.04063    7.61
## Workers                       0.10601    0.03821    2.77
## LifeCycleCouple w/o children -1.11616    0.09390  -11.89
## LifeCycleEmpty Nester        -0.83680    0.09753   -8.58
## LifeCycleSingle              -1.16063    0.12386   -9.37
## Age0to14                      0.35660    0.03072   11.61
## D1B                           0.02310    0.00770    3.00
## D2A_EPHHM                     0.34220    0.12682    2.70
## D3bpo4                        0.00355    0.00119    2.99
##                                          Pr(>|z|)    
## (Intercept)                  < 0.0000000000000002 ***
## AADVMT                          0.000000032794116 ***
## LogIncome                       0.000000000000027 ***
## Workers                                    0.0055 ** 
## LifeCycleCouple w/o children < 0.0000000000000002 ***
## LifeCycleEmpty Nester        < 0.0000000000000002 ***
## LifeCycleSingle              < 0.0000000000000002 ***
## Age0to14                     < 0.0000000000000002 ***
## D1B                                        0.0027 ** 
## D2A_EPHHM                                  0.0070 ** 
## D3bpo4                                     0.0028 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
## 
## Number of iterations in BFGS optimization: 37 
## Log-likelihood: -1.13e+04 on 22 Df

Population Density (D1B) Sensitivity

The elasticity estimates of bike person miles traveled per household with respect to population density (D1B) is negative due to the negative D1B coefficient in the model specification. Alternative model specifications have been tested with other density variables (D1C - job density, D1D - activity density) and interactions with D2 variables, the negative coefficient has been persistent.

The elasticities are the largest for the densest (>10,000 person/sq mile) non-metro areas, with density increases 50%, the bike PMT more than doubled for households living in these areas.

  Δ BikePMT wrt Δ D1B
metro Category n BikePMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.1708   -0.002 -0.004 -0.005 -0.007 -0.009
non_metro 65023 0.1519   0.002 0.003 0.005 0.007 0.009
population_per_sqm
metro <1k 7755 0.1324   0.000 0.000 0.000 -0.001 -0.001
metro 1k-5k 38783 0.1614   -0.001 -0.002 -0.002 -0.003 -0.004
metro 5k-10k 18000 0.1893   -0.002 -0.004 -0.006 -0.008 -0.010
metro >10k 8375 0.1841   -0.006 -0.011 -0.016 -0.021 -0.026
non_metro <1k 45003 0.1311   0.000 0.000 0.001 0.001 0.001
non_metro 1k-5k 16470 0.1833   0.002 0.005 0.007 0.010 0.012
non_metro 5k-10k 3101 0.2521   0.009 0.017 0.027 0.036 0.046
non_metro >10k 449 0.4678   0.081 0.177 0.292 0.427 0.588
Income
metro <$40k 26484 0.0874   -0.001 -0.002 -0.003 -0.004 -0.005
metro $40k-$80k 22503 0.1496   -0.002 -0.003 -0.005 -0.006 -0.007
metro >$80k 23926 0.2523   -0.003 -0.005 -0.008 -0.010 -0.013
non_metro <$40k 27719 0.0839   0.002 0.003 0.005 0.008 0.010
non_metro $40k-$80k 21443 0.1592   0.001 0.003 0.004 0.006 0.007
non_metro >$80k 15861 0.2505   0.002 0.004 0.006 0.009 0.011
DevelopmentType
metro Employment 13440 0.1586   -0.001 -0.002 -0.003 -0.004 -0.005
metro Low Density/Rural 7204 0.1450   0.000 -0.001 -0.001 -0.002 -0.002
metro Mixed 4183 0.1972   -0.002 -0.004 -0.007 -0.009 -0.011
metro Mixed High 998 0.1929   -0.004 -0.008 -0.011 -0.014 -0.018
metro Residential 46503 0.1683   -0.002 -0.004 -0.006 -0.007 -0.009
metro TOD 585 0.5680   -0.021 -0.040 -0.059 -0.076 -0.092
non_metro Employment 11873 0.1674   0.001 0.003 0.004 0.005 0.007
non_metro Low Density/Rural 37061 0.1301   0.001 0.002 0.003 0.004 0.006
non_metro Mixed 356 0.2285   0.008 0.018 0.028 0.038 0.051
non_metro Mixed High 80 0.2117   0.008 0.017 0.027 0.037 0.049
non_metro Residential 15647 0.1906   0.004 0.007 0.011 0.015 0.019
non_metro TOD 6 0.4015   0.026 0.055 0.087 0.122 0.160

Household AADVMT Sensitivity

To capture the relationship between driving and usage of other modes, we include AADVMT in models of non-driving modes. Bike PMT consistenly has a negative elasticity to AADVMT with relatively little variations across segments.

  Δ BikePMT wrt Δ AADVMT
metro Category n BikePMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.1708   -0.003 -0.006 -0.008 -0.011 -0.014
non_metro 65023 0.1519   -0.003 -0.006 -0.009 -0.012 -0.015
population_per_sqm
metro <1k 7755 0.1324   -0.003 -0.005 -0.008 -0.010 -0.012
metro 1k-5k 38783 0.1614   -0.003 -0.006 -0.008 -0.011 -0.013
metro 5k-10k 18000 0.1893   -0.003 -0.006 -0.009 -0.012 -0.015
metro >10k 8375 0.1841   -0.002 -0.005 -0.007 -0.010 -0.012
non_metro <1k 45003 0.1311   -0.003 -0.006 -0.008 -0.011 -0.014
non_metro 1k-5k 16470 0.1833   -0.003 -0.007 -0.010 -0.013 -0.016
non_metro 5k-10k 3101 0.2521   -0.004 -0.009 -0.013 -0.017 -0.021
non_metro >10k 449 0.4678   -0.006 -0.011 -0.016 -0.022 -0.027
Income
metro <$40k 26484 0.0874   -0.001 -0.002 -0.003 -0.004 -0.005
metro $40k-$80k 22503 0.1496   -0.002 -0.005 -0.007 -0.009 -0.011
metro >$80k 23926 0.2523   -0.005 -0.009 -0.014 -0.018 -0.022
non_metro <$40k 27719 0.0839   -0.001 -0.002 -0.003 -0.004 -0.006
non_metro $40k-$80k 21443 0.1592   -0.003 -0.006 -0.009 -0.012 -0.015
non_metro >$80k 15861 0.2505   -0.006 -0.012 -0.018 -0.023 -0.029
DevelopmentType
metro Employment 13440 0.1586   -0.003 -0.005 -0.008 -0.010 -0.013
metro Low Density/Rural 7204 0.1450   -0.003 -0.006 -0.008 -0.011 -0.014
metro Mixed 4183 0.1972   -0.003 -0.006 -0.008 -0.011 -0.014
metro Mixed High 998 0.1929   -0.002 -0.005 -0.007 -0.010 -0.012
metro Residential 46503 0.1683   -0.003 -0.006 -0.008 -0.011 -0.014
metro TOD 585 0.5680   -0.005 -0.011 -0.016 -0.021 -0.026
non_metro Employment 11873 0.1674   -0.003 -0.006 -0.010 -0.013 -0.016
non_metro Low Density/Rural 37061 0.1301   -0.003 -0.006 -0.008 -0.011 -0.014
non_metro Mixed 356 0.2285   -0.004 -0.007 -0.011 -0.015 -0.018
non_metro Mixed High 80 0.2117   -0.003 -0.006 -0.010 -0.013 -0.016
non_metro Residential 15647 0.1906   -0.004 -0.007 -0.010 -0.014 -0.017
non_metro TOD 6 0.4015   -0.003 -0.006 -0.010 -0.013 -0.016

Household Income Sensitivity

Bike PMT has a positive elasticity to household income.

  Δ BikePMT wrt Δ income
metro Category n BikePMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.1708   0.005 0.009 0.013 0.017 0.020
non_metro 65023 0.1519   0.010 0.021 0.031 0.040 0.050
population_per_sqm
metro <1k 7755 0.1324   0.003 0.007 0.010 0.013 0.015
metro 1k-5k 38783 0.1614   0.004 0.008 0.012 0.016 0.019
metro 5k-10k 18000 0.1893   0.005 0.010 0.014 0.018 0.022
metro >10k 8375 0.1841   0.005 0.010 0.014 0.018 0.022
non_metro <1k 45003 0.1311   0.009 0.018 0.026 0.035 0.043
non_metro 1k-5k 16470 0.1833   0.013 0.025 0.037 0.049 0.060
non_metro 5k-10k 3101 0.2521   0.017 0.034 0.051 0.067 0.083
non_metro >10k 449 0.4678   0.030 0.060 0.089 0.116 0.144
Income
metro <$40k 26484 0.0874   0.002 0.004 0.006 0.008 0.010
metro $40k-$80k 22503 0.1496   0.004 0.008 0.011 0.015 0.018
metro >$80k 23926 0.2523   0.007 0.013 0.019 0.025 0.030
non_metro <$40k 27719 0.0839   0.006 0.011 0.017 0.022 0.027
non_metro $40k-$80k 21443 0.1592   0.011 0.022 0.032 0.042 0.052
non_metro >$80k 15861 0.2505   0.017 0.034 0.051 0.067 0.083
DevelopmentType
metro Employment 13440 0.1586   0.004 0.008 0.012 0.015 0.019
metro Low Density/Rural 7204 0.1450   0.004 0.007 0.011 0.014 0.017
metro Mixed 4183 0.1972   0.005 0.010 0.015 0.019 0.023
metro Mixed High 998 0.1929   0.005 0.010 0.014 0.019 0.023
metro Residential 46503 0.1683   0.004 0.009 0.013 0.016 0.020
metro TOD 585 0.5680   0.015 0.030 0.043 0.056 0.068
non_metro Employment 11873 0.1674   0.012 0.023 0.034 0.044 0.055
non_metro Low Density/Rural 37061 0.1301   0.009 0.018 0.026 0.034 0.043
non_metro Mixed 356 0.2285   0.016 0.031 0.046 0.061 0.075
non_metro Mixed High 80 0.2117   0.015 0.029 0.043 0.057 0.070
non_metro Residential 15647 0.1906   0.013 0.026 0.038 0.051 0.063
non_metro TOD 6 0.4015   0.028 0.056 0.083 0.109 0.135

Freeway Supply Sensitivity

  Δ BikePMT wrt Δ FwyLaneMiPC
metro Category n BikePMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.1708   -0.007 -0.013 -0.020 -0.026 -0.031
population_per_sqm
metro <1k 7755 0.1324   -0.006 -0.011 -0.017 -0.022 -0.026
metro 1k-5k 38783 0.1614   -0.007 -0.013 -0.019 -0.025 -0.031
metro 5k-10k 18000 0.1893   -0.007 -0.014 -0.021 -0.028 -0.034
metro >10k 8375 0.1841   -0.007 -0.013 -0.020 -0.026 -0.032
Income
metro <$40k 26484 0.0874   -0.003 -0.007 -0.010 -0.013 -0.016
metro $40k-$80k 22503 0.1496   -0.006 -0.012 -0.017 -0.022 -0.028
metro >$80k 23926 0.2523   -0.010 -0.020 -0.029 -0.038 -0.046
DevelopmentType
metro Employment 13440 0.1586   -0.007 -0.013 -0.019 -0.024 -0.030
metro Low Density/Rural 7204 0.1450   -0.006 -0.012 -0.018 -0.023 -0.028
metro Mixed 4183 0.1972   -0.008 -0.015 -0.022 -0.029 -0.035
metro Mixed High 998 0.1929   -0.007 -0.014 -0.021 -0.027 -0.033
metro Residential 46503 0.1683   -0.007 -0.013 -0.019 -0.025 -0.031
metro TOD 585 0.5680   -0.021 -0.041 -0.060 -0.078 -0.096

Transit Supply Sensitivity

  Δ BikePMT wrt Δ TranRevMiPC
metro Category n BikePMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.1708   0.001 0.003 0.006 0.012 0.021
population_per_sqm
metro <1k 7755 0.1324   -0.001 -0.002 -0.003 -0.004 -0.004
metro 1k-5k 38783 0.1614   -0.001 -0.001 -0.001 0.000 0.001
metro 5k-10k 18000 0.1893   0.000 -0.001 -0.001 -0.001 -0.001
metro >10k 8375 0.1841   0.011 0.027 0.051 0.088 0.146
Income
metro <$40k 26484 0.0874   0.000 0.001 0.003 0.005 0.008
metro $40k-$80k 22503 0.1496   0.000 0.000 0.000 0.001 0.002
metro >$80k 23926 0.2523   0.003 0.007 0.015 0.027 0.047
DevelopmentType
metro Employment 13440 0.1586   -0.001 -0.001 -0.002 -0.002 -0.003
metro Low Density/Rural 7204 0.1450   -0.001 -0.002 -0.004 -0.005 -0.006
metro Mixed 4183 0.1972   0.001 0.003 0.005 0.007 0.010
metro Mixed High 998 0.1929   0.001 0.001 0.002 0.003 0.003
metro Residential 46503 0.1683   0.000 -0.001 -0.001 0.000 0.000
metro TOD 585 0.5680   0.158 0.398 0.769 1.356 2.294

Transit PMT

Model specification

The specification for the Transit PMT model has been documented in Task2. Here it is replicated for a quick reference.

## $metro
## 
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Transit) ~ AADVMT + Workers + 
##     LogIncome + VehPerDriver + LifeCycle + Age0to14 + CENSUS_R + 
##     D1B + D2A_EPHHM + FwyLaneMiPC + TranRevMiPC + D4c + D5 + D3bpo4 | 
##     AADVMT + Workers + LogIncome + LifeCycle + Age0to14 + CENSUS_R + 
##         D1B:D2A_EPHHM + D3bpo4 + D5 + TranRevMiPC + TranRevMiPC:D4c, 
##     data = ., na.action = na.exclude, weights = .$hhwgt)
## 
## Pearson residuals:
##      Min       1Q   Median       3Q      Max 
##  -6.9402  -0.2563  -0.1328  -0.0688 128.5624 
## 
## Count model coefficients (truncated poisson with log link):
##                                  Estimate   Std. Error z value
## (Intercept)                     1.3968934    0.0506707   27.57
## AADVMT                          0.0010530    0.0000867   12.15
## Workers                         0.0348845    0.0044274    7.88
## LogIncome                       0.1433907    0.0044881   31.95
## VehPerDriver                   -0.1942173    0.0107764  -18.02
## LifeCycleCouple w/o children    0.1447269    0.0093129   15.54
## LifeCycleEmpty Nester           0.0408172    0.0140119    2.91
## LifeCycleSingle                -0.0711508    0.0167510   -4.25
## Age0to14                       -0.0248657    0.0040674   -6.11
## CENSUS_RNE                      0.0867016    0.0104438    8.30
## CENSUS_RS                       0.1154482    0.0099818   11.57
## CENSUS_RW                       0.0436822    0.0103840    4.21
## D1B                             0.0015231    0.0000903   16.86
## D2A_EPHHM                       0.1428161    0.0151227    9.44
## FwyLaneMiPC                  -483.4617054   18.8991667  -25.58
## TranRevMiPC                     4.2314301    0.2934659   14.42
## D4c                             0.0007555    0.0000297   25.45
## D5                             -0.0182501    0.0005917  -30.84
## D3bpo4                         -0.0014674    0.0001007  -14.57
##                                          Pr(>|z|)    
## (Intercept)                  < 0.0000000000000002 ***
## AADVMT                       < 0.0000000000000002 ***
## Workers                        0.0000000000000033 ***
## LogIncome                    < 0.0000000000000002 ***
## VehPerDriver                 < 0.0000000000000002 ***
## LifeCycleCouple w/o children < 0.0000000000000002 ***
## LifeCycleEmpty Nester                      0.0036 ** 
## LifeCycleSingle                0.0000216113138666 ***
## Age0to14                       0.0000000009751348 ***
## CENSUS_RNE                   < 0.0000000000000002 ***
## CENSUS_RS                    < 0.0000000000000002 ***
## CENSUS_RW                      0.0000259134214371 ***
## D1B                          < 0.0000000000000002 ***
## D2A_EPHHM                    < 0.0000000000000002 ***
## FwyLaneMiPC                  < 0.0000000000000002 ***
## TranRevMiPC                  < 0.0000000000000002 ***
## D4c                          < 0.0000000000000002 ***
## D5                           < 0.0000000000000002 ***
## D3bpo4                       < 0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
##                               Estimate Std. Error z value
## (Intercept)                  -0.708854   0.214059   -3.31
## AADVMT                       -0.007184   0.000461  -15.59
## Workers                       0.423336   0.021651   19.55
## LogIncome                    -0.174968   0.019946   -8.77
## LifeCycleCouple w/o children -0.952405   0.045605  -20.88
## LifeCycleEmpty Nester        -1.528624   0.063059  -24.24
## LifeCycleSingle              -1.678198   0.067230  -24.96
## Age0to14                      0.416430   0.018681   22.29
## CENSUS_RNE                   -0.117512   0.049835   -2.36
## CENSUS_RS                    -0.009735   0.045683   -0.21
## CENSUS_RW                    -0.503523   0.047138  -10.68
## D3bpo4                        0.001098   0.000478    2.30
## D5                            0.022575   0.003331    6.78
## TranRevMiPC                  26.744452   1.284161   20.83
## D1B:D2A_EPHHM                 0.011163   0.001461    7.64
## TranRevMiPC:D4c               0.037776   0.004319    8.75
##                                          Pr(>|z|)    
## (Intercept)                               0.00093 ***
## AADVMT                       < 0.0000000000000002 ***
## Workers                      < 0.0000000000000002 ***
## LogIncome                    < 0.0000000000000002 ***
## LifeCycleCouple w/o children < 0.0000000000000002 ***
## LifeCycleEmpty Nester        < 0.0000000000000002 ***
## LifeCycleSingle              < 0.0000000000000002 ***
## Age0to14                     < 0.0000000000000002 ***
## CENSUS_RNE                                0.01837 *  
## CENSUS_RS                                 0.83125    
## CENSUS_RW                    < 0.0000000000000002 ***
## D3bpo4                                    0.02165 *  
## D5                              0.000000000012205 ***
## TranRevMiPC                  < 0.0000000000000002 ***
## D1B:D2A_EPHHM                   0.000000000000021 ***
## TranRevMiPC:D4c              < 0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
## 
## Number of iterations in BFGS optimization: 41 
## Log-likelihood: -8.4e+04 on 35 Df
## 
## $non_metro
## 
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Transit) ~ AADVMT + HhSize + 
##     LogIncome + VehPerDriver + LifeCycle + Age0to14 + Age65Plus + 
##     CENSUS_R + D1B + D1B:D2A_EPHHM + D3bmm4 | AADVMT + Workers + 
##     LogIncome + HhSize + Age0to14 + CENSUS_R + D3bmm4 + D1B + D1B:D2A_EPHHM, 
##     data = ., na.action = na.exclude, weights = .$hhwgt)
## 
## Pearson residuals:
##      Min       1Q   Median       3Q      Max 
## -12.4581  -0.1661  -0.0890  -0.0502 139.5826 
## 
## Count model coefficients (truncated poisson with log link):
##                                Estimate Std. Error z value
## (Intercept)                   0.9194978  0.0596973   15.40
## AADVMT                        0.0007485  0.0000664   11.28
## HhSize                        0.2131211  0.0033743   63.16
## LogIncome                     0.0984393  0.0052552   18.73
## VehPerDriver                  0.1918384  0.0068071   28.18
## LifeCycleCouple w/o children  0.8616579  0.0199820   43.12
## LifeCycleEmpty Nester         0.6639761  0.0242690   27.36
## LifeCycleSingle               0.9675740  0.0365964   26.44
## Age0to14                     -0.0530107  0.0045495  -11.65
## Age65Plus                     0.0801120  0.0108367    7.39
## CENSUS_RNE                   -0.0582363  0.0117882   -4.94
## CENSUS_RS                    -0.0022070  0.0088806   -0.25
## CENSUS_RW                    -0.3119044  0.0124618  -25.03
## D1B                           0.0094453  0.0024589    3.84
## D3bmm4                       -0.0066420  0.0010582   -6.28
## D1B:D2A_EPHHM                -0.0826449  0.0051319  -16.10
##                                          Pr(>|z|)    
## (Intercept)                  < 0.0000000000000002 ***
## AADVMT                       < 0.0000000000000002 ***
## HhSize                       < 0.0000000000000002 ***
## LogIncome                    < 0.0000000000000002 ***
## VehPerDriver                 < 0.0000000000000002 ***
## LifeCycleCouple w/o children < 0.0000000000000002 ***
## LifeCycleEmpty Nester        < 0.0000000000000002 ***
## LifeCycleSingle              < 0.0000000000000002 ***
## Age0to14                     < 0.0000000000000002 ***
## Age65Plus                        0.00000000000014 ***
## CENSUS_RNE                       0.00000078032870 ***
## CENSUS_RS                                 0.80373    
## CENSUS_RW                    < 0.0000000000000002 ***
## D1B                                       0.00012 ***
## D3bmm4                           0.00000000034612 ***
## D1B:D2A_EPHHM                < 0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
##                Estimate Std. Error z value             Pr(>|z|)    
## (Intercept)   -4.845286   0.285463  -16.97 < 0.0000000000000002 ***
## AADVMT         0.000841   0.000348    2.42              0.01564 *  
## Workers        0.167486   0.024236    6.91      0.0000000000048 ***
## LogIncome      0.036775   0.026458    1.39              0.16454    
## HhSize         0.467070   0.016865   27.69 < 0.0000000000000002 ***
## Age0to14       0.559119   0.024405   22.91 < 0.0000000000000002 ***
## CENSUS_RNE     0.094263   0.061732    1.53              0.12677    
## CENSUS_RS     -0.178302   0.046972   -3.80              0.00015 ***
## CENSUS_RW     -0.535953   0.061787   -8.67 < 0.0000000000000002 ***
## D3bmm4        -0.019728   0.004463   -4.42      0.0000098674287 ***
## D1B           -0.051344   0.013044   -3.94      0.0000827745547 ***
## D1B:D2A_EPHHM  0.086518   0.025021    3.46              0.00054 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
## 
## Number of iterations in BFGS optimization: 29 
## Log-likelihood: -6.05e+04 on 28 Df

Population Density (D1B) Sensitivity

  Δ TransitPMT wrt Δ D1B
metro Category n TransitPMT   +10% +20% +30% +40% +50%
overall
metro 72913 1.373   0.011 0.023 0.035 0.048 0.060
non_metro 65023 1.601   -0.007 -0.015 -0.022 -0.029 -0.036
population_per_sqm
metro <1k 7755 1.154   0.001 0.001 0.002 0.003 0.004
metro 1k-5k 38783 1.219   0.003 0.007 0.010 0.014 0.017
metro 5k-10k 18000 1.256   0.008 0.015 0.023 0.030 0.038
metro >10k 8375 2.233   0.052 0.105 0.160 0.216 0.274
non_metro <1k 45003 1.804   -0.002 -0.005 -0.007 -0.010 -0.012
non_metro 1k-5k 16470 1.207   -0.016 -0.032 -0.048 -0.064 -0.079
non_metro 5k-10k 3101 0.825   -0.030 -0.058 -0.086 -0.112 -0.138
non_metro >10k 449 0.549   -0.033 -0.065 -0.093 -0.120 -0.145
Income
metro <$40k 26484 0.935   0.009 0.018 0.027 0.036 0.046
metro $40k-$80k 22503 1.236   0.010 0.021 0.032 0.043 0.055
metro >$80k 23926 1.822   0.014 0.029 0.044 0.059 0.075
non_metro <$40k 27719 1.037   -0.005 -0.009 -0.014 -0.018 -0.023
non_metro $40k-$80k 21443 1.739   -0.008 -0.015 -0.022 -0.030 -0.037
non_metro >$80k 15861 2.313   -0.011 -0.023 -0.034 -0.044 -0.055
DevelopmentType
metro Employment 13440 1.384   0.007 0.014 0.021 0.028 0.035
metro Low Density/Rural 7204 1.181   0.001 0.003 0.004 0.005 0.007
metro Mixed 4183 1.456   0.015 0.031 0.047 0.063 0.079
metro Mixed High 998 2.249   0.085 0.172 0.262 0.354 0.449
metro Residential 46503 1.340   0.011 0.022 0.033 0.045 0.057
metro TOD 585 3.169   0.078 0.158 0.239 0.322 0.406
non_metro Employment 11873 1.478   -0.009 -0.017 -0.026 -0.034 -0.042
non_metro Low Density/Rural 37061 1.797   -0.003 -0.006 -0.009 -0.012 -0.015
non_metro Mixed 356 0.786   -0.023 -0.046 -0.068 -0.088 -0.108
non_metro Mixed High 80 0.365   -0.011 -0.021 -0.031 -0.041 -0.050
non_metro Residential 15647 1.245   -0.016 -0.033 -0.048 -0.064 -0.079
non_metro TOD 6 0.180   -0.005 -0.009 -0.013 -0.017 -0.021

Household AADVMT Sensitivity

  Δ TransitPMT wrt Δ AADVMT
metro Category n TransitPMT   +10% +20% +30% +40% +50%
overall
metro 72913 1.373   -0.040 -0.079 -0.116 -0.152 -0.187
non_metro 65023 1.601   0.021 0.043 0.065 0.087 0.110
population_per_sqm
metro <1k 7755 1.154   -0.043 -0.083 -0.122 -0.160 -0.196
metro 1k-5k 38783 1.219   -0.040 -0.078 -0.115 -0.151 -0.186
metro 5k-10k 18000 1.256   -0.038 -0.074 -0.109 -0.143 -0.176
metro >10k 8375 2.233   -0.043 -0.086 -0.127 -0.167 -0.206
non_metro <1k 45003 1.804   0.025 0.050 0.076 0.102 0.129
non_metro 1k-5k 16470 1.207   0.014 0.028 0.043 0.058 0.073
non_metro 5k-10k 3101 0.825   0.010 0.019 0.029 0.039 0.049
non_metro >10k 449 0.549   0.004 0.009 0.013 0.018 0.022
Income
metro <$40k 26484 0.935   -0.019 -0.037 -0.055 -0.072 -0.089
metro $40k-$80k 22503 1.236   -0.035 -0.068 -0.100 -0.132 -0.162
metro >$80k 23926 1.822   -0.061 -0.119 -0.175 -0.229 -0.282
non_metro <$40k 27719 1.037   0.010 0.021 0.032 0.043 0.054
non_metro $40k-$80k 21443 1.739   0.023 0.047 0.071 0.095 0.120
non_metro >$80k 15861 2.313   0.036 0.072 0.110 0.148 0.187
DevelopmentType
metro Employment 13440 1.384   -0.042 -0.083 -0.122 -0.160 -0.196
metro Low Density/Rural 7204 1.181   -0.044 -0.087 -0.128 -0.167 -0.204
metro Mixed 4183 1.456   -0.037 -0.073 -0.108 -0.141 -0.174
metro Mixed High 998 2.249   -0.034 -0.068 -0.101 -0.132 -0.164
metro Residential 46503 1.340   -0.039 -0.077 -0.114 -0.149 -0.183
metro TOD 585 3.169   -0.048 -0.094 -0.140 -0.185 -0.229
non_metro Employment 11873 1.478   0.019 0.037 0.057 0.076 0.096
non_metro Low Density/Rural 37061 1.797   0.025 0.050 0.076 0.103 0.130
non_metro Mixed 356 0.786   0.008 0.016 0.024 0.033 0.041
non_metro Mixed High 80 0.365   0.004 0.008 0.013 0.017 0.022
non_metro Residential 15647 1.245   0.015 0.029 0.044 0.060 0.075
non_metro TOD 6 0.180   0.002 0.003 0.005 0.006 0.008

Household Income Sensitivity

  Δ TransitPMT wrt Δ income
metro Category n TransitPMT   +10% +20% +30% +40% +50%
overall
metro 72913 1.373   0.000 0.000 0.000 0.001 0.001
non_metro 65023 1.601   0.020 0.038 0.054 0.070 0.085
population_per_sqm
metro <1k 7755 1.154   -0.001 -0.001 -0.001 -0.002 -0.002
metro 1k-5k 38783 1.219   0.000 -0.001 -0.001 -0.002 -0.002
metro 5k-10k 18000 1.256   0.000 -0.001 -0.001 -0.001 -0.002
metro >10k 8375 2.233   0.004 0.007 0.011 0.014 0.016
non_metro <1k 45003 1.804   0.022 0.042 0.061 0.079 0.096
non_metro 1k-5k 16470 1.207   0.015 0.029 0.041 0.053 0.064
non_metro 5k-10k 3101 0.825   0.010 0.019 0.028 0.036 0.044
non_metro >10k 449 0.549   0.007 0.013 0.018 0.023 0.028
Income
metro <$40k 26484 0.935   0.000 0.000 0.000 0.000 0.000
metro $40k-$80k 22503 1.236   0.000 0.000 0.000 0.000 0.000
metro >$80k 23926 1.822   0.001 0.001 0.001 0.002 0.002
non_metro <$40k 27719 1.037   0.013 0.025 0.036 0.046 0.056
non_metro $40k-$80k 21443 1.739   0.021 0.041 0.059 0.076 0.092
non_metro >$80k 15861 2.313   0.028 0.054 0.078 0.101 0.122
DevelopmentType
metro Employment 13440 1.384   0.000 0.000 0.000 -0.001 -0.001
metro Low Density/Rural 7204 1.181   -0.001 -0.001 -0.002 -0.002 -0.003
metro Mixed 4183 1.456   0.000 0.000 0.000 0.000 0.000
metro Mixed High 998 2.249   0.007 0.014 0.020 0.026 0.031
metro Residential 46503 1.340   0.000 0.000 0.000 0.000 0.000
metro TOD 585 3.169   0.009 0.017 0.025 0.032 0.038
non_metro Employment 11873 1.478   0.018 0.035 0.050 0.065 0.079
non_metro Low Density/Rural 37061 1.797   0.022 0.042 0.061 0.079 0.095
non_metro Mixed 356 0.786   0.010 0.018 0.027 0.034 0.042
non_metro Mixed High 80 0.365   0.005 0.009 0.013 0.017 0.020
non_metro Residential 15647 1.245   0.015 0.029 0.043 0.055 0.066
non_metro TOD 6 0.180   0.002 0.004 0.006 0.008 0.010

Freeway Supply Sensitivity

  Δ TransitPMT wrt Δ FwyLaneMiPC
metro Category n TransitPMT   +10% +20% +30% +40% +50%
overall
metro 72913 1.373   -0.037 -0.072 -0.107 -0.140 -0.172
population_per_sqm
metro <1k 7755 1.154   -0.034 -0.068 -0.100 -0.131 -0.160
metro 1k-5k 38783 1.219   -0.034 -0.068 -0.100 -0.131 -0.161
metro 5k-10k 18000 1.256   -0.033 -0.066 -0.097 -0.127 -0.157
metro >10k 8375 2.233   -0.052 -0.103 -0.152 -0.201 -0.248
Income
metro <$40k 26484 0.935   -0.025 -0.049 -0.073 -0.096 -0.118
metro $40k-$80k 22503 1.236   -0.033 -0.066 -0.097 -0.128 -0.157
metro >$80k 23926 1.822   -0.048 -0.095 -0.140 -0.184 -0.227
DevelopmentType
metro Employment 13440 1.384   -0.038 -0.074 -0.110 -0.144 -0.178
metro Low Density/Rural 7204 1.181   -0.035 -0.068 -0.101 -0.132 -0.162
metro Mixed 4183 1.456   -0.038 -0.075 -0.111 -0.146 -0.181
metro Mixed High 998 2.249   -0.051 -0.101 -0.150 -0.198 -0.244
metro Residential 46503 1.340   -0.035 -0.070 -0.103 -0.136 -0.167
metro TOD 585 3.169   -0.080 -0.157 -0.233 -0.307 -0.378

Transit Supply Sensitivity

  Δ TransitPMT wrt Δ TranRevMiPC
metro Category n TransitPMT   +10% +20% +30% +40% +50%
overall
metro 72913 1.373   0.101 0.210 0.326 0.451 0.585
population_per_sqm
metro <1k 7755 1.154   0.076 0.157 0.245 0.339 0.439
metro 1k-5k 38783 1.219   0.078 0.161 0.251 0.346 0.448
metro 5k-10k 18000 1.256   0.087 0.181 0.281 0.388 0.503
metro >10k 8375 2.233   0.219 0.457 0.712 0.985 1.278
Income
metro <$40k 26484 0.935   0.063 0.130 0.202 0.279 0.362
metro $40k-$80k 22503 1.236   0.087 0.181 0.282 0.391 0.507
metro >$80k 23926 1.822   0.142 0.294 0.458 0.633 0.819
DevelopmentType
metro Employment 13440 1.384   0.100 0.207 0.323 0.447 0.579
metro Low Density/Rural 7204 1.181   0.073 0.152 0.237 0.327 0.424
metro Mixed 4183 1.456   0.115 0.240 0.373 0.517 0.670
metro Mixed High 998 2.249   0.180 0.371 0.574 0.789 1.015
metro Residential 46503 1.340   0.098 0.204 0.318 0.439 0.569
metro TOD 585 3.169   0.330 0.682 1.056 1.449 1.863

Walk PMT

Model specification

The specification for the Bike PMT model has been documented in Task2. Here it is replicated for a quick reference.

## $metro
## 
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Walk) ~ AADVMT + Workers + 
##     LogIncome + VehPerDriver + LifeCycle + Age0to14 + CENSUS_R + 
##     D1B + D2A_EPHHM + FwyLaneMiPC + TranRevMiPC:D4c + D5 + D3apo | 
##     AADVMT + Workers + LogIncome + LifeCycle + Age0to14 + CENSUS_R + 
##         D1B:D2A_EPHHM + D3apo + D5 + TranRevMiPC, data = ., na.action = na.exclude, 
##     weights = .$hhwgt)
## 
## Pearson residuals:
##     Min      1Q  Median      3Q     Max 
## -6.8215 -0.4480 -0.2391  0.0718 51.7264 
## 
## Count model coefficients (truncated poisson with log link):
##                                Estimate Std. Error z value
## (Intercept)                   -0.596925   0.110574   -5.40
## AADVMT                         0.001578   0.000158    9.98
## Workers                        0.068028   0.009465    7.19
## LogIncome                      0.074321   0.009257    8.03
## VehPerDriver                  -0.151092   0.018988   -7.96
## LifeCycleCouple w/o children  -0.035200   0.019375   -1.82
## LifeCycleEmpty Nester         -0.124616   0.025034   -4.98
## LifeCycleSingle               -0.475727   0.032175  -14.79
## Age0to14                       0.133135   0.008171   16.29
## CENSUS_RNE                     0.048620   0.021734    2.24
## CENSUS_RS                     -0.059372   0.022520   -2.64
## CENSUS_RW                      0.079812   0.020692    3.86
## D1B                            0.000303   0.000248    1.22
## D2A_EPHHM                      0.038470   0.032372    1.19
## FwyLaneMiPC                  -20.149955  32.500687   -0.62
## D5                             0.006643   0.000900    7.38
## D3apo                          0.013995   0.001030   13.58
## TranRevMiPC:D4c                0.000389   0.002203    0.18
##                                          Pr(>|z|)    
## (Intercept)                   0.00000006723543680 ***
## AADVMT                       < 0.0000000000000002 ***
## Workers                       0.00000000000065942 ***
## LogIncome                     0.00000000000000099 ***
## VehPerDriver                  0.00000000000000176 ***
## LifeCycleCouple w/o children              0.06926 .  
## LifeCycleEmpty Nester         0.00000064267001481 ***
## LifeCycleSingle              < 0.0000000000000002 ***
## Age0to14                     < 0.0000000000000002 ***
## CENSUS_RNE                                0.02528 *  
## CENSUS_RS                                 0.00838 ** 
## CENSUS_RW                                 0.00011 ***
## D1B                                       0.22220    
## D2A_EPHHM                                 0.23469    
## FwyLaneMiPC                               0.53527    
## D5                            0.00000000000016064 ***
## D3apo                        < 0.0000000000000002 ***
## TranRevMiPC:D4c                           0.85989    
## Zero hurdle model coefficients (binomial with logit link):
##                               Estimate Std. Error z value
## (Intercept)                  -1.730454   0.148971  -11.62
## AADVMT                       -0.003185   0.000279  -11.43
## Workers                       0.188077   0.014898   12.62
## LogIncome                     0.040863   0.013591    3.01
## LifeCycleCouple w/o children -0.367228   0.028854  -12.73
## LifeCycleEmpty Nester        -0.590055   0.033665  -17.53
## LifeCycleSingle              -0.721178   0.034678  -20.80
## Age0to14                      0.234953   0.015637   15.03
## CENSUS_RNE                    0.069644   0.032723    2.13
## CENSUS_RS                    -0.048277   0.029543   -1.63
## CENSUS_RW                     0.179580   0.028942    6.20
## D3apo                         0.018510   0.001562   11.85
## D5                            0.042998   0.004210   10.21
## TranRevMiPC                   8.674384   0.855645   10.14
## D1B:D2A_EPHHM                 0.014234   0.001615    8.81
##                                          Pr(>|z|)    
## (Intercept)                  < 0.0000000000000002 ***
## AADVMT                       < 0.0000000000000002 ***
## Workers                      < 0.0000000000000002 ***
## LogIncome                                  0.0026 ** 
## LifeCycleCouple w/o children < 0.0000000000000002 ***
## LifeCycleEmpty Nester        < 0.0000000000000002 ***
## LifeCycleSingle              < 0.0000000000000002 ***
## Age0to14                     < 0.0000000000000002 ***
## CENSUS_RNE                                 0.0333 *  
## CENSUS_RS                                  0.1022    
## CENSUS_RW                           0.00000000055 ***
## D3apo                        < 0.0000000000000002 ***
## D5                           < 0.0000000000000002 ***
## TranRevMiPC                  < 0.0000000000000002 ***
## D1B:D2A_EPHHM                < 0.0000000000000002 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
## 
## Number of iterations in BFGS optimization: 39 
## Log-likelihood: -5.63e+04 on 33 Df
## 
## $non_metro
## 
## Call:
## pscl::hurdle(formula = int_cround(td.miles.Walk) ~ AADVMT + HhSize + 
##     LogIncome + VehPerDriver + LifeCycle + Age0to14 + Age65Plus + 
##     CENSUS_R + D1B + D1B:D2A_EPHHM + D3bpo4 | AADVMT + Workers + 
##     LogIncome + HhSize + Age0to14 + CENSUS_R + D3apo + D5, data = ., 
##     na.action = na.exclude, weights = .$hhwgt)
## 
## Pearson residuals:
##     Min      1Q  Median      3Q     Max 
## -4.3313 -0.3020 -0.1661 -0.0764 35.0914 
## 
## Count model coefficients (truncated poisson with log link):
##                               Estimate Std. Error z value
## (Intercept)                  -1.435987   0.144029   -9.97
## AADVMT                       -0.000243   0.000207   -1.17
## HhSize                        0.058387   0.009955    5.87
## LogIncome                     0.159945   0.012693   12.60
## VehPerDriver                 -0.058067   0.018809   -3.09
## LifeCycleCouple w/o children  0.033676   0.029915    1.13
## LifeCycleEmpty Nester         0.253318   0.035646    7.11
## LifeCycleSingle               0.258747   0.042474    6.09
## Age0to14                      0.082278   0.013558    6.07
## Age65Plus                    -0.120327   0.019623   -6.13
## CENSUS_RNE                   -0.046959   0.030663   -1.53
## CENSUS_RS                    -0.122348   0.024467   -5.00
## CENSUS_RW                     0.101452   0.025156    4.03
## D1B                          -0.032239   0.004998   -6.45
## D3bpo4                       -0.002106   0.000509   -4.14
## D1B:D2A_EPHHM                 0.090030   0.007911   11.38
##                                          Pr(>|z|)    
## (Intercept)                  < 0.0000000000000002 ***
## AADVMT                                      0.240    
## HhSize                            0.0000000044817 ***
## LogIncome                    < 0.0000000000000002 ***
## VehPerDriver                                0.002 ** 
## LifeCycleCouple w/o children                0.260    
## LifeCycleEmpty Nester             0.0000000000012 ***
## LifeCycleSingle                   0.0000000011155 ***
## Age0to14                          0.0000000012904 ***
## Age65Plus                         0.0000000008675 ***
## CENSUS_RNE                                  0.126    
## CENSUS_RS                         0.0000005715884 ***
## CENSUS_RW                         0.0000550735773 ***
## D1B                               0.0000000001120 ***
## D3bpo4                            0.0000350674863 ***
## D1B:D2A_EPHHM                < 0.0000000000000002 ***
## Zero hurdle model coefficients (binomial with logit link):
##              Estimate Std. Error z value             Pr(>|z|)    
## (Intercept) -3.496908   0.163075  -21.44 < 0.0000000000000002 ***
## AADVMT      -0.000759   0.000239   -3.17               0.0015 ** 
## Workers      0.061349   0.015200    4.04    0.000054364064470 ***
## LogIncome    0.154760   0.015459   10.01 < 0.0000000000000002 ***
## HhSize       0.156757   0.010996   14.26 < 0.0000000000000002 ***
## Age0to14     0.050910   0.019273    2.64               0.0083 ** 
## CENSUS_RNE   0.152501   0.037688    4.05    0.000052016240971 ***
## CENSUS_RS   -0.185892   0.028801   -6.45    0.000000000108760 ***
## CENSUS_RW    0.352937   0.032581   10.83 < 0.0000000000000002 ***
## D3apo        0.015708   0.002013    7.80    0.000000000000006 ***
## D5          -0.065921   0.021396   -3.08               0.0021 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 
## 
## Number of iterations in BFGS optimization: 29 
## Log-likelihood: -4.11e+04 on 27 Df

Population Density (D1B) Sensitivity

  Δ WalkPMT wrt Δ D1B
metro Category n WalkPMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.580   0.003 0.005 0.008 0.011 0.013
non_metro 65023 0.400   0.001 0.001 0.002 0.003 0.004
population_per_sqm
metro <1k 7755 0.411   0.000 0.000 0.001 0.001 0.001
metro 1k-5k 38783 0.496   0.001 0.002 0.004 0.005 0.006
metro 5k-10k 18000 0.625   0.003 0.006 0.008 0.011 0.014
metro >10k 8375 0.849   0.009 0.017 0.025 0.034 0.042
non_metro <1k 45003 0.369   0.000 0.000 0.000 0.000 0.001
non_metro 1k-5k 16470 0.445   0.001 0.003 0.004 0.006 0.007
non_metro 5k-10k 3101 0.607   0.003 0.007 0.011 0.015 0.019
non_metro >10k 449 0.610   0.010 0.021 0.034 0.048 0.064
Income
metro <$40k 26484 0.460   0.003 0.005 0.008 0.010 0.013
metro $40k-$80k 22503 0.549   0.003 0.005 0.008 0.010 0.013
metro >$80k 23926 0.697   0.003 0.005 0.008 0.011 0.014
non_metro <$40k 27719 0.308   0.000 0.001 0.002 0.002 0.003
non_metro $40k-$80k 21443 0.420   0.001 0.001 0.002 0.003 0.004
non_metro >$80k 15861 0.521   0.001 0.002 0.003 0.004 0.005
DevelopmentType
metro Employment 13440 0.523   0.002 0.004 0.007 0.009 0.011
metro Low Density/Rural 7204 0.446   0.000 0.001 0.001 0.001 0.002
metro Mixed 4183 0.644   0.005 0.010 0.014 0.019 0.024
metro Mixed High 998 0.940   0.011 0.022 0.033 0.043 0.054
metro Residential 46503 0.587   0.002 0.005 0.007 0.010 0.012
metro TOD 585 1.131   0.012 0.024 0.036 0.047 0.059
non_metro Employment 11873 0.404   0.002 0.004 0.006 0.009 0.011
non_metro Low Density/Rural 37061 0.371   0.000 0.000 0.000 0.000 0.000
non_metro Mixed 356 0.585   0.012 0.025 0.039 0.053 0.069
non_metro Mixed High 80 0.495   0.013 0.027 0.042 0.058 0.076
non_metro Residential 15647 0.464   0.001 0.002 0.003 0.004 0.005
non_metro TOD 6 0.286   0.010 0.021 0.034 0.048 0.063

Household AADVMT Sensitivity

  Δ WalkPMT wrt Δ AADVMT
metro Category n WalkPMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.580   -0.004 -0.007 -0.011 -0.015 -0.019
non_metro 65023 0.400   -0.002 -0.004 -0.006 -0.008 -0.010
population_per_sqm
metro <1k 7755 0.411   -0.004 -0.008 -0.012 -0.016 -0.020
metro 1k-5k 38783 0.496   -0.004 -0.008 -0.012 -0.016 -0.020
metro 5k-10k 18000 0.625   -0.004 -0.008 -0.011 -0.015 -0.019
metro >10k 8375 0.849   -0.003 -0.005 -0.008 -0.011 -0.014
non_metro <1k 45003 0.369   -0.002 -0.004 -0.006 -0.008 -0.010
non_metro 1k-5k 16470 0.445   -0.002 -0.004 -0.006 -0.008 -0.010
non_metro 5k-10k 3101 0.607   -0.002 -0.005 -0.007 -0.010 -0.012
non_metro >10k 449 0.610   -0.002 -0.004 -0.006 -0.008 -0.010
Income
metro <$40k 26484 0.460   -0.002 -0.005 -0.007 -0.009 -0.011
metro $40k-$80k 22503 0.549   -0.004 -0.007 -0.011 -0.014 -0.018
metro >$80k 23926 0.697   -0.005 -0.010 -0.015 -0.020 -0.025
non_metro <$40k 27719 0.308   -0.001 -0.002 -0.003 -0.004 -0.005
non_metro $40k-$80k 21443 0.420   -0.002 -0.004 -0.006 -0.009 -0.011
non_metro >$80k 15861 0.521   -0.003 -0.006 -0.010 -0.013 -0.016
DevelopmentType
metro Employment 13440 0.523   -0.004 -0.007 -0.011 -0.015 -0.019
metro Low Density/Rural 7204 0.446   -0.004 -0.009 -0.013 -0.018 -0.022
metro Mixed 4183 0.644   -0.003 -0.007 -0.010 -0.014 -0.017
metro Mixed High 998 0.940   -0.002 -0.004 -0.005 -0.007 -0.009
metro Residential 46503 0.587   -0.004 -0.008 -0.011 -0.015 -0.019
metro TOD 585 1.131   0.000 -0.001 -0.001 -0.001 -0.002
non_metro Employment 11873 0.404   -0.002 -0.004 -0.006 -0.008 -0.009
non_metro Low Density/Rural 37061 0.371   -0.002 -0.004 -0.006 -0.008 -0.010
non_metro Mixed 356 0.585   -0.002 -0.005 -0.007 -0.009 -0.012
non_metro Mixed High 80 0.495   -0.002 -0.004 -0.006 -0.008 -0.010
non_metro Residential 15647 0.464   -0.002 -0.004 -0.006 -0.008 -0.010
non_metro TOD 6 0.286   -0.001 -0.002 -0.002 -0.003 -0.004

Household Income Sensitivity

  Δ WalkPMT wrt Δ income
metro Category n WalkPMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.580   0.004 0.008 0.011 0.014 0.017
non_metro 65023 0.400   0.008 0.016 0.023 0.030 0.036
population_per_sqm
metro <1k 7755 0.411   0.003 0.005 0.008 0.010 0.012
metro 1k-5k 38783 0.496   0.003 0.007 0.009 0.012 0.015
metro 5k-10k 18000 0.625   0.004 0.008 0.012 0.016 0.019
metro >10k 8375 0.849   0.006 0.011 0.016 0.020 0.025
non_metro <1k 45003 0.369   0.008 0.015 0.021 0.027 0.033
non_metro 1k-5k 16470 0.445   0.009 0.017 0.025 0.033 0.040
non_metro 5k-10k 3101 0.607   0.012 0.023 0.034 0.044 0.054
non_metro >10k 449 0.610   0.012 0.024 0.035 0.045 0.054
Income
metro <$40k 26484 0.460   0.003 0.006 0.008 0.011 0.013
metro $40k-$80k 22503 0.549   0.004 0.007 0.010 0.013 0.016
metro >$80k 23926 0.697   0.005 0.009 0.014 0.018 0.021
non_metro <$40k 27719 0.308   0.006 0.012 0.017 0.022 0.027
non_metro $40k-$80k 21443 0.420   0.009 0.017 0.024 0.031 0.038
non_metro >$80k 15861 0.521   0.011 0.021 0.030 0.039 0.048
DevelopmentType
metro Employment 13440 0.523   0.004 0.007 0.010 0.013 0.015
metro Low Density/Rural 7204 0.446   0.003 0.006 0.009 0.011 0.013
metro Mixed 4183 0.644   0.004 0.008 0.012 0.016 0.019
metro Mixed High 998 0.940   0.006 0.012 0.017 0.022 0.026
metro Residential 46503 0.587   0.004 0.008 0.011 0.014 0.018
metro TOD 585 1.131   0.007 0.014 0.020 0.026 0.032
non_metro Employment 11873 0.404   0.008 0.016 0.024 0.030 0.037
non_metro Low Density/Rural 37061 0.371   0.008 0.015 0.021 0.028 0.033
non_metro Mixed 356 0.585   0.013 0.025 0.036 0.047 0.057
non_metro Mixed High 80 0.495   0.011 0.022 0.032 0.041 0.050
non_metro Residential 15647 0.464   0.009 0.018 0.026 0.034 0.041
non_metro TOD 6 0.286   0.007 0.013 0.019 0.025 0.030

Freeway Supply Sensitivity

  Δ WalkPMT wrt Δ FwyLaneMiPC
metro Category n WalkPMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.580   0.000 -0.001 -0.001 -0.002 -0.002
population_per_sqm
metro <1k 7755 0.411   0.000 -0.001 -0.001 -0.001 -0.002
metro 1k-5k 38783 0.496   0.000 -0.001 -0.001 -0.001 -0.002
metro 5k-10k 18000 0.625   0.000 -0.001 -0.001 -0.002 -0.002
metro >10k 8375 0.849   -0.001 -0.001 -0.002 -0.002 -0.003
Income
metro <$40k 26484 0.460   0.000 -0.001 -0.001 -0.001 -0.001
metro $40k-$80k 22503 0.549   0.000 -0.001 -0.001 -0.002 -0.002
metro >$80k 23926 0.697   -0.001 -0.001 -0.002 -0.002 -0.003
DevelopmentType
metro Employment 13440 0.523   0.000 -0.001 -0.001 -0.002 -0.002
metro Low Density/Rural 7204 0.446   0.000 -0.001 -0.001 -0.001 -0.002
metro Mixed 4183 0.644   0.000 -0.001 -0.001 -0.002 -0.002
metro Mixed High 998 0.940   -0.001 -0.001 -0.002 -0.003 -0.003
metro Residential 46503 0.587   0.000 -0.001 -0.001 -0.002 -0.002
metro TOD 585 1.131   -0.001 -0.002 -0.002 -0.003 -0.004

Transit Supply Sensitivity

  Δ WalkPMT wrt Δ TranRevMiPC
metro Category n WalkPMT   +10% +20% +30% +40% +50%
overall
metro 72913 0.580   0.007 0.014 0.021 0.028 0.035
population_per_sqm
metro <1k 7755 0.411   0.005 0.009 0.014 0.019 0.024
metro 1k-5k 38783 0.496   0.005 0.011 0.017 0.022 0.028
metro 5k-10k 18000 0.625   0.007 0.014 0.022 0.029 0.036
metro >10k 8375 0.849   0.012 0.023 0.035 0.047 0.058
Income
metro <$40k 26484 0.460   0.005 0.011 0.016 0.022 0.027
metro $40k-$80k 22503 0.549   0.006 0.013 0.019 0.026 0.032
metro >$80k 23926 0.697   0.008 0.017 0.025 0.033 0.042
DevelopmentType
metro Employment 13440 0.523   0.006 0.013 0.019 0.025 0.032
metro Low Density/Rural 7204 0.446   0.005 0.010 0.015 0.020 0.025
metro Mixed 4183 0.644   0.008 0.016 0.024 0.032 0.040
metro Mixed High 998 0.940   0.009 0.019 0.028 0.037 0.046
metro Residential 46503 0.587   0.007 0.014 0.021 0.028 0.035
metro TOD 585 1.131   0.010 0.021 0.031 0.042 0.052

Phase II

The models (AADVMT model, trip frequency model and person mile traveled model for bike, walk, and transit) are applied to RVMPO data using the visioneval framework with RSPM/VisionEval sythesized households and supplemental block group built environment level inputs. Below are the model prediction outputs, and compared with related results from OHAS for RVMPO. Comparing with RSPM VMT/Alt mode trips output is to be accomplished.

Predictions from the New Models

  Trips  PMT
Category n AADVMT   BikeTrips WalkTrips TransitTrips   BikePMT WalkPMT TransitPMT
Overall
RVMPO 74045 41.800   0.146 0.891 0.144   0.290 0.578 0.751
DevelopmentType
Rural 6476 49.200   0.158 0.754 0.134   0.294 0.513 0.816
Urban 67569 41.100   0.145 0.905 0.145   0.290 0.584 0.745
Income
<$40k 31432 25.100   0.124 0.762 0.180   0.167 0.482 0.676
$40k-$80k 18071 43.800   0.149 0.907 0.125   0.288 0.586 0.754
>$80k 24542 61.800   0.172 1.045 0.111   0.449 0.694 0.844
Popuplation per Square Mile
<1k 19126 42.300   0.143 0.710 0.133   0.249 0.476 0.739
1k-5k 35477 42.300   0.144 0.898 0.141   0.294 0.579 0.753
5k-10k 18211 40.700   0.151 1.071 0.157   0.327 0.682 0.757
>10k 1231 36.900   0.157 0.876 0.202   0.258 0.575 0.792

RSPM Predictions

TODO

OHAS

Those are the weighted average trip and person mile traveled per household by mode from the 2012 Oregon Household Activity Survey for RVMPO.

  Trips  PMT
n Category   BikeT DrivingT TransitT WalkT   BikeM DrivingM TransitM WalkM
Overall
1119 RVMPO   0.206 8.100 0.109 0.879   0.360 36.600 0.591 0.285
Income
367 <$40k   0.138 6.500 0.144 0.798   0.164 27.200 0.762 0.222
329 $40k-$80k   0.455 9.200 0.014 0.777   0.763 39.100 0.050 0.313
235 >$80k   0.072 8.970 0.114 1.186   0.300 53.900 0.845 0.336

Phase III

All modules in the VETravelDemand R package have been tested to work with the develop branch of VisionEval using the RVMPO data. Automated testing (continuous integration) have been put in place to make sure the code/package passes all tests and is in working condition with the latest version of VisionEval all the time. And if anything breaks automated tests, authors of the packages will be notified through email (see also Task 3).